title: Complete stability in multistable delayed neural networks.
abstract: We investigate the complete stability for multistable delayed neural networks. A new formulation modified from the previous studies on multistable networks is developed to derive componentwise dynamical property. An iteration argument is then constructed to conclude that every solution of the network converges to a single equilibrium as time tends to infinity. The existence of 3n equilibria and 2n positively invariant sets for the n-neuron system remains valid under the new formulation. The theory is demonstrated by a numerical illustration.
authors.affiliation: Department of Applied Mathematics, National Pingtung University of Education, Pingtung, Taiwan 900, ROC. cycheng@mail.npue.edu.tw
authors.forename: Chang-Yuan
authors.initials: CY
authors.lastname: Cheng
authors.forename: Chih-Wen
authors.initials: CW
authors.lastname: Shih
mesh_terms: D000818:Animals; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics